Esse banco de dados é de um resultado de um projeto de Ciência cidadã feito em Arraial do Cabo. A fotos recebidas foram utilizadas para identificação individual das tartarugas marinhas através do método de foto-identificação. O software utilizado para as comparações foi o Hotspotter, com intermédio do Internet of Turtles. Os dados podem ser encontrados no Internet of Turtles procurando pelo ID “isabellaferreira”. Para esse trabalho foram extraídos os encontros (avistamento de um único animal em um local e horário específicos) registrados até a data atual.
Carregando os pacotes
library(readxl)
## Warning: package 'readxl' was built under R version 4.0.5
library(tidyverse)
## Warning: package 'tidyverse' was built under R version 4.0.5
## Warning: package 'ggplot2' was built under R version 4.0.5
## Warning: package 'tibble' was built under R version 4.0.5
## Warning: package 'tidyr' was built under R version 4.0.5
## Warning: package 'readr' was built under R version 4.0.5
## Warning: package 'purrr' was built under R version 4.0.5
## Warning: package 'dplyr' was built under R version 4.0.5
## Warning: package 'stringr' was built under R version 4.0.5
## Warning: package 'forcats' was built under R version 4.0.5
library(stringr)
library(psych)
## Warning: package 'psych' was built under R version 4.0.5
library(lubridate)
## Warning: package 'lubridate' was built under R version 4.0.5
library(plyr)
## Warning: package 'plyr' was built under R version 4.0.5
library(plotly)
## Warning: package 'plotly' was built under R version 4.0.5
Abrindo a tabela e selecionando as colunas
originalenctable <- read_excel("encounterSearchResults_export_isabellaferreira.xls") %>%
select(Name0.value, Occurrence.occurrenceID, Encounter.verbatimLocality,Encounter.year,Encounter.month,Encounter.day, Encounter.behavior,Encounter.genus,Encounter.specificEpithet,Encounter.occurrenceRemarks,Encounter.mediaAsset0,Encounter.mediaAsset1)
Analisando a tabela
lapply(originalenctable, unique)
## $Name0.value
## [1] "MdT344" "MdT316" "MdT6" "MdT342" "MdT72"
## [6] "MdT343" "MdT341" "MdT314" "MdT345" "MdT311"
## [11] "MdT312" "MdT310" "MdT313" "MdT303" "MdT304"
## [16] "MdT294" "Bicuda" "MdT308" "MdT307" "MdT295"
## [21] "MdT296" "MdT293" "MdT292" "MdT291" "MdT300"
## [26] "MdT290" "MdT289" "MdT299" "MdT288" "MdT287"
## [31] "MdT285" "MdT286" "MdT346" "MdT330" "MdT326"
## [36] "MdT325" "MdT327" "MdT328" "MdT329" "MdT302"
## [41] "MdT320" "MdT324" "MdT322" "MdT323" "MdT321"
## [46] "MdT319" "MdT261" "MdT335" "MdT333" "MdT78"
## [51] "MdT339" "MdT33" "MdT340" "MdT253" "MdT331"
## [56] "MdT334" "MdT338" "MdT336" "MdT348" "MdT262"
## [61] "MdT259" "MdT337" "MdT309" "MdT305" "MdT306"
## [66] "MdT284" "MdT280" "MdT317" "MdT315" "MdT282"
## [71] "MdT283" "MdT318" "MdT277" "MdT276" "MdT275"
## [76] "MdT278" "MdT271" "MdT272" "MdT273" "MdT274"
## [81] "MdT279" "MdT270" "MdT269" "MdT268" "MdT298"
## [86] "MdT266" "MdT265" "MdT267" "MdT264" "MdT263"
## [91] "MdT75" "Rachel" "MdT251" "MdT250" "MdT24"
## [96] "MdT86" "MdT249" "MdT252" "MdT260" "MdT256"
## [101] "MdT254" "MdT257" "MdT255" "MdT258" "MdT206"
## [106] "MdT243" "MdT237" "MdT159" "MdT105" "MdT83"
## [111] "MdT28" "MdT244" "MdT126" "MdT248" "MdT229"
## [116] "MdT224" "MdT100" "Fafa" "MdT54" "MdT221"
## [121] "MdT222" "MdT226" "MdT84" "MdT236" "MdT179"
## [126] "MdT146" "Margarida" "Tikinha" "Dorminhoca" "MdT234"
## [131] "MdT183" "MdT150" "MdT87" "MdT90" "MdT246"
## [136] "MdT141" "MdT135" "MdT124" "MdT68" "Drika"
## [141] "MdT136" "MdT127" "MdT191" "MdT155" "MdT40"
## [146] "MdT202" "MdT149" "MdT162" "MdT77" "MdT138"
## [151] "MdT74" "MdT82" "MdT140" "MdT184" "MdT185"
## [156] "MdT247" "MdT200" "MdT80" "Judite" "MdT134"
## [161] "MdT347" "MdT301" "MdT148" "MdT115" "MdT139"
## [166] "MdT73" "MdT114" "MdT192" "MdT130" "MdT228"
## [171] "MdT175" "MdT76" "MdT238" "MdT147" "MdT142"
## [176] "MdT132" "MdT106" "MdT39" "MdT89" "MdT181"
## [181] "MdT182" "MdT92" "MdT217" "MdT97" "MdT117"
## [186] "MdT31" "MdT52" "MdT55" "Josimar" "MdT133"
## [191] "MdT194" "MdT193" "MdT204" "MdT203" "MdT36"
## [196] "MdT225" "MdT154" "MdT165" "MdT50" "MdT196"
## [201] "MdT241" "MdT239" "MdT79" "MdT151" "MdT164"
## [206] "MdT161" "MdT102" "MdT101" "MdT93" "MdT190"
## [211] "MdT49" "MdT96" "MdT110" "MdT176" "MdT48"
## [216] "MdT116" "MdT240" "MdT98" "MdT88" "MdT111"
## [221] "MdT137" "MdT107" "Brava" "MdT177" "MdT157"
## [226] "MdT156" "MdT220" "MdT119" "MdT47" "MdT218"
## [231] "MdT208" "MdT212" "MdT143" "MdT216" "MdT118"
## [236] "MdT153" "MdT213" "MdT103" "MdT211" "MdT209"
## [241] "MdT219" "MdT201" "MdT95" "MdT35" "MdT104"
## [246] "MdT170" "MdT123" "MdT46" "MdT125" "MdT172"
## [251] "MdT169" "MdT71" "MdT242" "MdT160" "MdT158"
## [256] "MdT199" "MdT45" "MdT163" "MdT43" "MdT42"
## [261] "MdT41" "MdT231" "MdT109" "MdT94" "MdT128"
## [266] "MdT205" "MdT232" "MdT214" "MdT230" "MdT112"
## [271] "MdT227" "MdT233" "MdT197" "MdT129" "MdT166"
## [276] "MdT245" "MdT207" "MdT38" "MdT198" "MdT186"
## [281] "MdT62" "MdT37" "MdT34" "MdT32" "MdT187"
## [286] "MdT30" "MdT29" "MdT131" "MdT180" "MdT67"
## [291] "MdT66" "MdT27" "MdT26" "MdT64" "MdT168"
## [296] "MdT25" "MdT63" "MdT69" "MdT70" "MdT61"
## [301] "MdT22" "MdT23" "MdT21" "Aninha" "MdT235"
## [306] "MdT20" "MdT19" "MdT18" "MdT58" "MdT59"
## [311] "MdT60" "MdT17" "MdT15" "MdT16" "MdT13"
## [316] "MdT14" "MdT12" "MdT11" "MdT57" "MdT10"
## [321] "MdT8" "MdT9" "MdT7" "MdT5" "MdT3"
## [326] "MdT56" "MdT4" "MdT167" "MdT2" "MdT1"
## [331] "MdT53"
##
## $Occurrence.occurrenceID
## [1] "973de39d-ae5e-42ed-88d0-c434b407c08e"
## [2] "9ef424bc-29e9-4cbf-8694-40e8475860fb"
## [3] "e271bbfa-5602-444a-9a93-24638faedb88"
## [4] "351253c5-4502-4de2-9116-64be4880be19"
## [5] "7ffdc664-33b3-44b3-84e7-80a72577f956"
## [6] "74f7ef96-c924-466e-adb0-95444c301cfe"
## [7] "3402c99a-1ca8-43f3-b404-273425b539b0"
## [8] "ecf6ee74-3a23-4f4c-be1e-ec7d6f5798ef"
## [9] "0218cd5f-0fee-4ec3-b86f-73f4078f4e0e"
## [10] "4e0e877c-9205-4e61-826c-5adddd562280"
## [11] "930843de-ee99-4917-8bf6-53e81a68b0bf"
## [12] "cba1cd3b-337b-4af6-a466-12c0b5f1df9e"
## [13] "ddb8d6ad-48a5-4bac-adf2-143bccac97d6"
## [14] "6e1e8f49-877b-471f-8c3c-939d6d1c5584"
## [15] "ed790f9c-26bf-4f5d-911e-bfe825fa6b76"
## [16] "3475a627-73a9-40a3-b6c2-a634e2ca8e5a"
## [17] "f6e0e172-3b6e-405e-a99f-2d8e94d1c916"
## [18] "578d9740-246f-402a-8c81-b06c0157623a"
## [19] "853854a5-3f0a-423e-9e83-f56854006889"
## [20] "d6274bf0-759e-410c-98e9-739ce325b558"
## [21] "2b3bc78b-8b35-4820-8e29-cadde81b7c5d"
## [22] "9c9b8ef7-01fb-4901-9699-ddbe69d52441"
## [23] "485a0f19-b8da-4a77-9b51-74a415c88339"
## [24] "ee62b8b0-97b4-417a-84a1-70ccbd3eed5c"
## [25] "239c7e90-8a30-4671-b986-85803a3de6d0"
## [26] "76f19270-931b-46bd-a8bb-8a76859787a3"
## [27] "72248b37-03ef-40cb-bbf7-849bdaca7c0f"
## [28] "497fa259-ad2f-4458-8b8e-37d1c59923b1"
## [29] "3db0f325-5e9b-4a5d-9dd0-8296d8226b6e"
## [30] "f2c398ba-d5f9-441d-9842-ab39b0414106"
## [31] "bd39585e-eb8b-4fd3-81c8-0b81aadedddf"
## [32] "54dd65db-5a5e-4e1f-97d9-477c253443d4"
## [33] "10a43c8d-d344-456b-b5f1-1693fc651d26"
## [34] "62224628-7681-4166-8327-999229bdd02e"
## [35] "73deb8a0-be46-4741-aa04-fe2aee2d79e4"
## [36] "c118013f-ec09-4a96-a180-e87bf3e252c3"
## [37] "07ced264-39d9-4b60-87d5-0a7266fc3cf1"
## [38] "4d37bd87-7d78-4e0e-aa7f-343f83ab215d"
## [39] "549285f8-0c1d-4f25-a042-e0c96e9ba793"
## [40] "1457fc4d-eacf-4d01-bddc-ad455d13ce66"
## [41] "66b7752a-9da7-454d-a222-d564926020b4"
## [42] "b461abcf-6b4f-4f51-9900-e0ef64c85c05"
## [43] "9b2225ed-44cc-4ff1-8de1-b6a3a887b95d"
## [44] "ea9e1c60-2e4a-41b9-830d-b7080ba40725"
## [45] "bd44ee8e-cb99-49aa-9237-7c1fd9ab7c46"
## [46] "b53b58c3-be01-4554-8f98-219440bb8bb7"
## [47] "39e926d9-29fe-4c92-8222-caac4ee4b075"
## [48] "6d5b3e67-1ada-41c9-a401-21ad61ff1b03"
## [49] "7d722e89-d9ac-49cd-8b15-23202ba79a2b"
## [50] "188a512c-45ab-4280-a7e5-f8a1a6a5b0ab"
## [51] "c22c7d9d-8f98-4fa5-910e-9cc1db240042"
## [52] "595c88ae-a00c-4c8a-907f-fd84e6a3f75e"
## [53] "660f911c-c9a9-410b-b94f-0352ea816ffd"
## [54] "76b64337-1695-4834-a947-9d165ddf9188"
## [55] "76e33fbe-e990-4b38-8a71-f96781408019"
## [56] "7b29ddc3-80b9-463d-9473-b4062508f6f2"
## [57] "4dd55dad-dba1-4b72-a616-aab131f4c8ee"
## [58] "a13339eb-4a1f-4ac4-9fa3-54e98e5c24f1"
## [59] "a671973a-eb6c-43b8-9f8c-e79017aae71d"
## [60] "a243d263-a1ad-4fb1-a869-abf1bb8dd2b9"
## [61] "826d424b-10b5-4de9-9e79-6347cf777962"
## [62] "a67cc0ff-b75a-4abe-86c4-1e8376fabe77"
## [63] "c9388721-d0ac-4448-929f-211ab9221d6d"
## [64] "6666d2ea-023b-407d-a2af-2c7f65887aea"
## [65] "14aeb1a1-f127-42b2-9420-bc2ad51adadc"
## [66] "4b23bd80-2b61-47bd-8f9f-d119c9947592"
## [67] "715271aa-c177-4fec-882f-5b97508e1685"
## [68] "5dcb1370-aa23-4fb8-98b6-9f378472fa65"
## [69] "c1cbce80-213f-4e76-8a79-096f1b61865a"
## [70] "07013054-9c63-4f1b-bbc1-e0088f00869c"
## [71] "a9112bb1-40bf-445d-9890-0d6347c89d88"
## [72] "be15d993-13fd-496c-a209-13720b9e4c66"
## [73] "e443b793-8fd2-4d16-9cdc-7eee8b093dc5"
## [74] "21568d1d-096e-4eaf-8d3e-3507ec6927e5"
## [75] "21138f85-b905-452e-8751-f32854c4687f"
## [76] "247bde9a-028f-4f44-8b3a-dcd036469042"
## [77] "173deb25-eb90-421f-aaae-36bb1028f83b"
## [78] "b57c77b6-fe90-4743-a19c-afe2a300b29f"
## [79] "0e685b11-b20a-4697-94da-969d66d0fca1"
## [80] "850fb78b-3685-4d17-aabb-60f6cce9e6b8"
## [81] "c04cddaf-958a-49d4-aea0-1ae12bd1b5ae"
## [82] "7e5884f0-8501-41bd-a5a6-cda47b731b44"
## [83] "c21e1445-963d-46f0-b356-2b09baaf5ee3"
## [84] "8f8c9319-0bd4-4f53-ac63-80f156d3e255"
## [85] "ff73ae43-1c24-46fa-ab6a-e92e6815e392"
## [86] "ce523310-dc44-4e76-93ea-b1301186dbeb"
## [87] "2def5073-227a-461e-bcaa-9ee17b968118"
## [88] "1e05c12c-15e8-4141-a08f-e2235fbecead"
## [89] "e93523c3-f7c7-4dfc-a391-6ef68fe92043"
## [90] "d860e665-d8fe-4a7a-9eef-922d9c0bae8d"
## [91] "eed1958f-7910-4b0d-b18b-1069eabf72fd"
## [92] "3416e758-5569-4ee4-a0a1-9b74ce14ae13"
## [93] "7c415ee8-a947-44ad-a3c0-3d698816e4cd"
## [94] "63764a2d-c968-4054-9f70-328d0ce63be8"
## [95] "53eddd04-8641-4588-bd8d-1c559c734214"
## [96] "712a6a51-545b-434f-8b64-57f43c78b6bd"
## [97] "21da0257-d661-4cc3-8145-b8fbced6ceaa"
## [98] "13d8693e-741f-4d36-8b2d-c8858109bfdb"
## [99] "9349c548-0a7c-4c43-994f-3237a8c0e51a"
## [100] "5ac4a655-d4a9-4dbe-adc1-34f2249a8036"
## [101] "98e38830-04f7-4174-af8d-11f4abfd227d"
## [102] "422e8191-0cff-4f3d-9de4-2f55ea421624"
## [103] "47fd07a2-f786-4402-b65c-844ae8215cd8"
## [104] "400b9db2-cfb6-45fa-96f7-61c54f466e3c"
## [105] "9613d0dc-947a-4126-b685-7d371c921bfa"
## [106] "476ffa1c-0e56-42bf-978c-2cb2897574f6"
## [107] "1f84535b-8b71-4111-b24e-d103d74c6dcf"
## [108] "bf6f19a8-c476-4319-ad7d-ffddaf1f9793"
## [109] "f2ce2535-5fb1-4fab-b92b-dcf9a7140d26"
## [110] "9f230287-b2d1-44b4-9507-3e05a2c6b503"
## [111] "c8101b64-16a4-4d03-b332-0b73fbbb6068"
## [112] "42802e76-08ee-4bca-8daa-5232434d36b2"
## [113] "8f4865b5-fab4-4c8e-91b6-325c6c991a37"
## [114] "d4d8aacf-6e7c-4c37-bae8-1e4fabdff478"
## [115] "f2458ea3-9026-4cca-8e7d-4ee2dbc52e5d"
## [116] "1b33a653-9f48-4964-9b0b-1917ad6f68bb"
## [117] "5e9921d4-d973-4ba5-924b-a204ee581174"
## [118] "fae69a0d-3eb6-416a-9224-25f27d69f8e1"
## [119] "1d5da146-5bb0-45b6-9d12-aca2b8525ee1"
## [120] "90526516-26c5-42f6-b4c0-a99b92871bce"
## [121] "92c5007f-c145-4681-a533-ca6c772293cd"
## [122] "d55e9d0f-38db-4a21-853c-382c863e7c58"
## [123] "88a0c16d-325f-4393-977a-bd3b26709267"
## [124] "d2fc7511-b222-4e48-9acb-57f2e71537e5"
## [125] "5d8331b2-6804-4aeb-a367-961cf4b7fa3c"
## [126] "fce9711d-3bc0-40d2-ae86-618ea0d2aaa8"
## [127] "9e0daef8-6e0d-4f54-8f76-f23512646ce8"
## [128] "704b09b5-56e6-4342-80a0-8a03fbf7b28f"
## [129] "16a54671-9569-42af-ba0d-9b84dc7b129e"
## [130] "e7200334-2f5d-4275-b09a-2c72e4e43714"
## [131] "490a2ec4-1d69-454c-9d52-0dd49e3d9c15"
## [132] "9774c172-d64e-4a35-8d1e-8bf72c0a8c8e"
## [133] "8bf59c5c-18c4-4e3a-b644-f7a8d46fb830"
## [134] "472eb9ab-3bb3-401b-99d7-647873ec01f1"
## [135] "434b64c3-f1ae-46ea-b1b1-2beec78525b9"
## [136] "5849e726-a300-4421-bdc9-970077533ae3"
## [137] "703d6bb8-94f6-4bec-a2e6-a97a1ad28348"
## [138] "0ee085cb-32b8-4915-bcf5-72e16c62c2ed"
## [139] "8fec92f8-6e9b-421c-8ee8-5d1329803d15"
## [140] "aa5c5629-8262-4c84-a490-f1e4daa2907e"
## [141] "ff212e81-a589-4f97-8b51-9c72cb5fbc9b"
## [142] "34efeacb-0c7c-4d68-9ad7-20f7fa1d1fcd"
## [143] "f6025c1d-c6b8-4258-a361-3e0b7323e588"
## [144] "0ee850c5-6fe2-4bc2-a796-6a3b3d273d77"
## [145] "e7db63fc-1ac7-4968-8f9d-b43a267b66be"
## [146] "3ec31280-541f-47d7-82e0-d403c779046e"
## [147] "3587febe-7d11-45e9-930f-cdf23fa8075b"
## [148] "6ddd4296-5326-47a2-98a8-d04ce0aa8432"
## [149] "74a094ce-ecda-4a2d-a36c-33368c2cc8e9"
## [150] "bfe3cc4e-8d06-4aa0-bb69-a48a2d663ab0"
## [151] "5ded0be4-b79e-45d4-a18f-5a0ebfd348a9"
## [152] "97685e2a-990b-4bab-b510-5505dfd728f8"
## [153] "83bfbd9b-cc4b-409e-af1a-fbd318c2d6ca"
## [154] "e1a09b84-5373-4a9b-ab6f-de6dbfed1bed"
## [155] "4a07c062-16fe-42be-ac54-a7605e7e9fcd"
## [156] "62d48058-5e68-4448-af0f-8de55d14aa2c"
## [157] "62ef7f87-6942-439d-b406-255bf5622cfb"
## [158] "10461e35-40e6-486d-be00-f93fbfb45195"
## [159] "df541e7e-09b7-4e1f-9071-cd87cec766ff"
## [160] "2b183df1-3c49-4b56-8e5f-fe51f40f97d8"
## [161] "5c0be005-d862-477a-a7ec-40af8bf0f1f0"
## [162] "97891d67-f66d-42e1-a6df-7e74b8964751"
## [163] "1c0c4845-ed16-41e6-8218-ae4fd95d79d0"
## [164] "5e8e8510-e4fd-4006-9a5f-4b227fc1aa9a"
## [165] "18354111-bb2d-492c-9540-eb2ad96571eb"
## [166] "951619c1-cc01-4868-adb4-17a435ae4b24"
## [167] "01abde41-104e-46dd-8ffb-2cf2a1e14a9b"
## [168] "dc8ce722-3410-4628-9d5e-43c1cf15008f"
## [169] "22339789-4f4f-4271-9343-e11c50cb3b4f"
## [170] "2c9b0f5e-7251-4d57-9a28-056fbccf53a2"
## [171] "b5010f38-3e52-4ba7-9b3f-368ecde5cee9"
## [172] "c9a96470-e86f-45d7-800c-5cefef027966"
## [173] "c72549d5-e596-4c75-bb7d-54af98d6e804"
## [174] "f7ecc2af-a690-4fd3-baf4-d10a455127f9"
## [175] "15fe9141-a34f-49cd-b74b-be2bbbf85e6a"
## [176] "eb09fcf7-d619-4c37-b55e-2419661f840c"
## [177] "8a6ef496-ec21-4d19-a9cd-e96b7a422c5d"
## [178] "37506637-14c6-47b4-abd9-459cff3054c0"
## [179] "c81c1a6c-333a-4791-9af6-1a2ebb80d466"
## [180] "3e9f753e-5a97-4eba-89fa-dc9a795a3a55"
## [181] "d20f8177-4e44-48b9-9a71-98296ead2088"
## [182] "ffa64434-6809-4d61-8fea-6a26076ca84a"
## [183] "a2d89ad8-2572-4c08-b246-6930646efa33"
## [184] "be8b9d37-cf51-425c-ab16-6eb9ae398943"
## [185] "171af485-e3f2-45e1-ab53-e439af2aee1f"
## [186] "68fc9fcb-c233-4413-ba1b-2d7b6c2a591f"
## [187] "057f7678-db2a-4f6e-9695-ab2de4ca6e44"
## [188] "de89e421-df32-4fa5-a975-2d7d3e744275"
## [189] "e5bdac29-b761-4ea7-a5d5-1fb22f1c96f4"
## [190] "dfaeb469-9f84-457c-b216-9f75b956de85"
## [191] "1869fd7f-443b-499c-a7d3-3f0b5d2d2314"
## [192] "c28e478b-2c6a-4c89-af68-9709f6d3cb5f"
## [193] "523959c0-0d38-44d4-89e4-8a6ffd647b07"
## [194] "aa38a8cf-274f-4f48-90ac-5f82e5f5be69"
## [195] "42b0aa8e-679a-44c5-9675-e9d788e5f7b7"
## [196] "d6a94149-60a5-4135-8e08-fe30ed75beeb"
## [197] "7f731302-cc26-4505-ae0b-e89afc685542"
## [198] "a484e6ab-bc39-4135-b40f-e642f5a671c1"
## [199] "a5e3bbf9-a4f4-4d07-9581-212f6bb08343"
## [200] "9887ae86-804c-4308-86c4-371187a4dca9"
## [201] "6000a0d7-5cfb-489a-8f04-ae496ff6bd1a"
## [202] "2ba12dcb-4629-48be-a2cb-52bffca92688"
## [203] "7140f941-03cb-4989-837f-171a6debc1ca"
## [204] "92ea6732-ecdc-4efd-b292-818ae57c0bbb"
## [205] "135865a2-bc18-462b-a65f-398c6b808e2c"
## [206] "55dc91d9-210e-489e-8cc7-1dc6481d36c7"
## [207] "54244306-f349-461a-b0fd-4a8e135ff318"
## [208] "4f5e3d67-9efd-42a9-a169-c9ce82d2fa8e"
## [209] "88032314-83d0-4fe9-ab42-d5fc56217c93"
## [210] "46ebd159-4494-4fee-8774-aa54d659f515"
## [211] "1f892d91-d517-4618-b19f-f749129df4b1"
## [212] "45dd0614-2df5-48cc-baff-7bdb1ef532c0"
## [213] "19c154b0-4fff-4838-9de5-8eb04946fcbc"
## [214] "0b0c751b-f4cf-41ad-9ea9-670885798468"
## [215] "9a54a0aa-b884-4ee7-b936-5796c15b4271"
## [216] "295d275a-df56-4515-b4e2-605316d9c83f"
## [217] "0edb403b-af80-4196-9db3-10f40164c984"
## [218] "0e357782-7e55-4b6c-b32d-736819c45f07"
## [219] "960a5844-76d9-4bb7-a993-8a3539dc2ab5"
## [220] "a2c66c70-68eb-4c80-b2d3-3b8ec2b46449"
## [221] "d1f128bf-3930-4463-81d0-256763195a81"
## [222] "fde6f535-acf1-4ac2-9118-ff8a9984d252"
## [223] "f9886bbc-8083-42dd-97e6-60f04e5df074"
## [224] "3b979d54-4c86-4ba3-a980-12926f34fa68"
## [225] "9c8c458b-be9c-4cfa-a4e7-565f05a22475"
## [226] "9b8eb5c4-fcbd-438b-830a-37743bd99715"
## [227] "265dd34c-54f3-4c11-bbf7-b5a71af4ff8a"
## [228] "0344eb09-40fd-4217-b734-77772103e286"
## [229] "5af519d1-07ce-4a26-9ddb-1abf1022fd37"
## [230] "2f1aed65-f197-439a-aa9c-e3831c91dea0"
## [231] "1aacfda7-3cf2-4f57-b8ed-0396dffa3092"
## [232] "f54c5eae-a4c9-4511-b5e6-61176946374c"
## [233] "b81676a3-1423-49d7-8fb2-a3b0786a5a34"
## [234] "b1686525-7b6c-465f-8521-efab419ed90a"
## [235] "c4208156-d50c-4e79-a66a-e0c786948637"
## [236] "fe37004e-50af-4f92-bde0-8fe76c58e9e2"
## [237] "0c8ce375-d483-4e0a-9850-e80283a003dc"
## [238] "2f13803d-3e51-4e04-9e53-8cd97ec91fdb"
## [239] "008aac3e-1e22-4885-ad7b-34994c8f7892"
## [240] "fe08ade6-9945-47b5-a046-b7f34f8ffe40"
## [241] "5f6ef5d6-2cd8-48f6-9a10-27e02796dc61"
## [242] "cadc0db5-9b64-4b64-a351-398f35bc5abf"
## [243] "3c11ec47-868c-4dd8-b164-896ce326c0ec"
## [244] "e8538ff8-853f-4cbc-ab4a-9c647e08ed57"
## [245] "346afad4-a8fa-4876-888a-ad85918c5ef9"
## [246] "b08dc085-1c87-4130-aa89-13153678cfea"
## [247] "a0e60e81-71bd-4509-a28c-1108502aef90"
## [248] "7254286e-3b22-4d1a-8887-fb31ce499d32"
## [249] "428770da-5d7e-4f65-9756-207f214dc997"
## [250] "72aafb7a-9aff-484e-9c3c-1bdf9169aefa"
## [251] "a7c07bba-fd43-40d0-a4f2-37faf022cfbe"
## [252] "45c3aabe-7366-4ff4-9f79-f47b20447d62"
## [253] "841f0447-6e68-4621-ab1b-517206b771e2"
## [254] "69b0add5-4861-4d10-8524-2c5543fc872d"
## [255] "21ddcc5f-163a-4ac6-91ec-80767391dad5"
## [256] "f7b5a7c7-0da2-49ec-8802-e1f94347f2f1"
## [257] "ccefbfdd-ed91-4d24-a7d8-729b1c73ad7f"
## [258] "31af0884-dae0-4eff-9ecf-94246de3712d"
## [259] "fafc578b-fdc2-453a-8e77-c74dd0159707"
## [260] "a62f075a-2d8b-4947-81da-5fac55ccbadc"
## [261] "250f57c1-3233-4a44-9f20-6ef89bd11f18"
## [262] "5e4d98f1-a6a8-4a9b-b99f-74e36cde9507"
## [263] "37a646b5-44b2-42c0-b951-55b57fa96492"
## [264] "559e209a-9a10-454a-830f-6d7515e7f016"
## [265] "96cfa366-2536-452a-8254-373fb1f855be"
## [266] "0b0ef362-ea74-47cd-becf-0e9170368ffb"
## [267] "b7a70788-d139-4313-87c0-329a109048a1"
## [268] "0c1f599d-ab06-4a33-9d24-9d0e01c72790"
## [269] "87cc19f3-220a-4550-88d7-aef9e386b28c"
## [270] "f503412d-ff16-4c81-9399-cd82841b54e8"
## [271] "e1f6780b-6e0e-47e9-a1ba-e3c5fb2e5ad9"
## [272] "e6987ef8-0307-4155-b7dd-136adf66d6fd"
## [273] "e0ad7809-a9b3-4c22-b9cd-15225c8d41b3"
## [274] "b84c335a-f2c2-4f3a-ac37-65ffde7d6f31"
## [275] "bf9e9ef1-e348-4e27-b5d4-77d220c26754"
## [276] "294c14f3-1786-4fd0-982e-b71e56e554c0"
## [277] "0815ad5a-9cb0-4f79-9147-dd6cbf3f3ac2"
## [278] "3240616c-5c7e-4636-96c0-067fed27d785"
## [279] "86eecea5-b185-4667-9975-7835acf9e8cd"
## [280] "c83907f6-5dfa-4392-aac1-daabacf8c99a"
## [281] "108ef905-7f95-43bd-acda-f73c178dc4f6"
## [282] "caf6aee8-d98c-4f57-ae6d-8c8e4f4d52a8"
## [283] "f1fa19f8-1648-4f19-8fae-88574fc7078d"
## [284] "acdb9666-f715-4d6c-817d-3e22b9019633"
## [285] "12f5985b-dece-4eea-b5bf-8bcbe888461f"
## [286] "593003ae-fb8d-4fcb-9010-c1b0280bca4f"
## [287] "830158aa-5c95-43cf-83d5-f0bf9a98177a"
## [288] "1de8e5a3-5ce6-4ef7-a0c6-9fac8d5abf71"
## [289] "39055688-a0eb-470c-bf23-c40b7ee86699"
## [290] "32231c36-8151-48f1-8865-d47fe432dd4a"
## [291] "dfc7b433-8ddf-4893-8601-3507154d130a"
## [292] "94e72574-86d4-417c-bf40-e3c51c44c79f"
## [293] "c9d4f4f8-6f12-4d2b-8a30-ebbd88b82ea3"
## [294] "d293e752-f897-4b9c-a9f4-ee8b8c6ba97d"
## [295] "ab41ada6-7f56-49bd-98c0-e62b19584059"
## [296] "a5e7eebf-16c8-42e8-9263-636c5af7c999"
## [297] "646e3a54-7715-4fe3-ad50-a4df9404812f"
## [298] "de81ad70-d0ef-4955-b25b-3bac3167dd13"
## [299] "7874ec30-bd5b-42b4-bfa4-f5c9d8af89e1"
## [300] "2d6c9cba-23cf-4564-ab0f-2545370ea463"
## [301] "c0571621-7eb6-4f90-b726-289ac3d618ed"
## [302] "022bdc87-7d48-423a-b09c-46405cd3857b"
## [303] "64ae8a0e-0de4-4d0d-b8ec-538c86fe3fe0"
## [304] "7ecca5ef-0896-481b-8728-20ae61f97207"
## [305] "1a04d465-d5df-4489-9d2f-80f3eadca921"
## [306] "b5496138-f4b0-4844-a11e-0727b77f2e44"
## [307] "acd2c494-18c5-4a6f-88a3-4469e9b18222"
## [308] "b8ff7bd6-dad2-43b7-a823-25eb1d0fe757"
## [309] "d395bd09-10ac-4b5c-bdfc-a07df57709b0"
## [310] "9e7ad40d-602b-4d18-aabe-27bf2b916fd5"
## [311] "27ee90d8-42cb-47cf-ac97-85eb1a8c3a30"
## [312] "67908989-f48f-48ba-9cdd-7877537e2644"
## [313] "a1c571cc-559f-4f67-b423-5799fc7d3424"
## [314] "fa7affb5-7980-45e9-89d3-0c6d21999f6e"
## [315] "3e860f1c-9ebc-4450-8e54-7e9bb33bdc87"
## [316] "f5fa5d79-e451-49e9-9360-5722ffa92dec"
## [317] "d15cc030-fcca-460a-8b07-c5c721ae1d1f"
## [318] "1b292d2e-0399-47bb-b1da-16546d9afb5e"
## [319] "c5748379-68d9-4124-a3f0-aac51c2dfaf9"
## [320] "f6c26fcc-2c5e-4aa1-83cd-11753826c62a"
## [321] "0edafb31-3ddb-41ca-bffe-b341abddae2f"
## [322] "e92fa84a-b812-49c9-aa35-f0e4ee8d6ba4"
## [323] "b2dce7ef-397b-42ac-8d7c-c02b2adae142"
## [324] "f7244e88-230e-497a-9df2-19361b053762"
## [325] "72fac31a-2fb8-4afd-be0e-80c3b210dfd4"
## [326] "e83bea01-419e-40c7-ba6f-ea964ecf11fd"
## [327] "55878eaa-e861-41eb-a5e7-7f126a618a3d"
## [328] "3e3ec9c2-51a3-4f81-bda6-65584872eaed"
## [329] "9eb3348f-4611-44bb-9642-c604991a2cbb"
## [330] "0318b5a2-aea0-4b5e-8fcc-b5f2b0c6e2fa"
## [331] "f9c8c06d-5f12-44d9-bb7f-b46b511b1af7"
## [332] "4d048c65-0bd9-4366-98d9-18f4144af45b"
## [333] "cf154c3f-966a-4598-97ef-dbcad2f003d5"
## [334] "945babac-0dc3-4081-a687-629c69b2441d"
## [335] "3e197aa8-ba84-452a-b1a4-c544cc37371d"
## [336] "cb3ef596-6e39-402f-875a-398e916a8192"
## [337] "71158d6e-31a0-4e2c-89e6-dcc04ba549b9"
## [338] "c2b9df8d-dc23-4468-8904-4a505c19741c"
## [339] "e882db4f-3405-4c2d-8bf6-668c0afa67a5"
## [340] "d5032e62-7459-4f66-8edf-e88cb59202e3"
## [341] "ce74df30-d12f-4921-a4cc-3e27f9ea4955"
## [342] "ddddaae4-9796-4bae-87f1-3e179658ef76"
## [343] "29c74c1e-2e6b-4ec1-9a57-e64cd541fbc1"
## [344] "fad35f39-4670-45ca-912e-8d706dafaa82"
## [345] "31c2a794-1199-4ba8-9a8f-48bd26fe7b14"
## [346] "ff5490e1-8879-469d-a5f9-f48d9211238b"
## [347] "06fd2d38-1904-4b05-be0f-9605334c11f7"
## [348] "8151c99f-8b5b-4166-a83d-1c86efc55ff4"
## [349] "795daed4-8669-4968-b2cf-dca99dd9dbab"
## [350] "8d7cb1c7-27e6-4314-925c-942628ad6e95"
## [351] "58dcbe29-2429-4246-bd1d-b7bdd54c264b"
## [352] "c40246c1-f71c-4ec5-9508-27f0f2d0b18e"
## [353] "5169894b-6e4a-4149-a780-16c3f51e888e"
## [354] "72a07440-630e-4483-81ba-0690ecc20ab4"
## [355] "4969bcd9-ede7-4e61-bce6-26491ae9bd57"
## [356] "abc8bd87-eea4-42d2-9e7b-e8935deef61d"
## [357] "3abb3e6c-45de-44bd-937e-eb0c8e9765b2"
## [358] "5e3ea80b-3e89-4356-a86c-8e7e67cf40b7"
## [359] "b1e7b0af-6941-42ae-be29-1b8d5cbbe1f1"
## [360] "2ecbb445-3752-407e-b7ef-b25f13537872"
## [361] "aab279b6-6a05-42da-9f21-8bf0f64549d1"
## [362] "9d2065a1-c011-4a6b-bbf1-c534fd794d4f"
## [363] "18ce5d23-fba1-46d0-832a-df1ee986f94c"
## [364] "cf0c821d-d897-4c50-9fe8-30549f2b058e"
## [365] "41bb46a3-a199-4613-a805-0a7b9b160b36"
## [366] "69c1e685-6d29-4b05-b70b-67feeec10d14"
## [367] "9faf4fbc-22f3-49af-a7e5-6ba39a2020d5"
## [368] "ef00a397-6ee3-424d-a62b-b57d7165bbc5"
## [369] "e8ae8056-cc87-4257-9b18-de2a6246d95d"
## [370] "8a84a4fb-9e99-472f-81ee-b34d5e8aaddc"
## [371] "69278dbc-b1a8-4ce5-a7f3-9008e3fc79a2"
## [372] "b8a6655b-6168-4d11-9879-961ef118fb0b"
## [373] "c6a37c32-27ff-4bb7-8767-8d75efc7fb94"
## [374] "fbc24b34-37f7-46d7-be8d-dd34b829b50a"
## [375] "c9c39ffe-02f6-491c-89fd-0644e231a359"
## [376] "66bc5a15-bff6-42df-bee4-d181c3f55cf7"
## [377] "d2f6196f-e835-497e-bccf-18edfe7c5a55"
## [378] "c6be523f-74b3-4416-a04d-5094fcd3f7a7"
## [379] "3257f846-da1e-4260-b536-24cabea0c023"
## [380] "9d746c6e-950a-4fda-b4b7-641f8da92fff"
## [381] "1549261e-97e0-4ae6-b8dc-56887ad8ec87"
## [382] "176013a5-ef33-4e7e-bb7a-1a89f06d4114"
## [383] "59d3580f-7a66-4419-84df-4abfa3133829"
## [384] "ca389774-fc21-4d13-945d-51e0a5c50297"
## [385] "8b76e6fd-88b7-40d5-9db3-f762ff52c82f"
## [386] "c88e5fd4-5d5f-42ad-b4de-5b2e835301c5"
## [387] "a09ba88b-57d6-42bc-99f8-e53037c665bf"
## [388] "bc803090-08b1-4a19-b3f7-193afc3785c5"
## [389] "49a47518-d35b-4321-9a29-6097af30b053"
## [390] "e7c017e4-1b5b-4352-a62e-c902080b4e95"
## [391] "07e4ae93-e91d-4849-bba6-2468474ff4c3"
## [392] "f26673c3-f2bb-41fa-a352-3a2878dad915"
## [393] "bb7097e8-189c-46aa-bdf3-ecdd8f19085d"
## [394] "a58f9f9e-c78c-4140-a31e-d6ba3890692e"
## [395] "8392dc86-02e9-4fbf-b5df-72bf1b39db73"
## [396] "25209eea-028b-4a57-be1c-d14345a0ed61"
## [397] "5afb7fc6-099e-4c3c-87cf-bb6fe067595a"
## [398] "ac1941c5-65d3-472f-920d-251180eae267"
## [399] "4a8c3e87-ecfe-4c87-a0d6-2ffb6e7b9506"
## [400] "c2716863-4368-43ba-9af5-4822dc234024"
## [401] "ee97e3b2-c9ea-42f1-87c4-fba10d62b175"
## [402] "32246824-b9d9-4b49-9635-cc89af1014c6"
## [403] "42da127b-46ef-4b61-ac53-df9b45aa2419"
## [404] "9853d444-a41f-4aa8-ac94-8d6566fc0f5e"
## [405] "ea25c04a-53b7-4cb2-97a3-cb8a75e0d982"
## [406] "12eb164e-b916-4871-9657-db06d988629e"
## [407] "6cef4db3-ab6b-439f-849a-9b15f2b9d697"
## [408] "eb8e81c7-b970-4337-87e6-5ae367bcc31e"
## [409] "90621308-9b54-4f36-ac86-1dac3d741f6f"
## [410] "4e4e585e-32aa-4575-84f7-107cc26d6b2e"
## [411] "0b43ccfc-6b2d-4457-991e-f1d56050f19d"
## [412] "010604ad-e6b1-4358-a5f0-371469ea5069"
## [413] "66b3cd18-1f5e-4f9b-b757-82276cdad37c"
## [414] "f130d7ae-77a2-4c40-95f8-ae9e2348987b"
## [415] "bc678ebc-fac4-4d9d-ab1a-740d548abcd5"
## [416] "932b55a2-fd24-4019-bfca-9180db0a5afc"
## [417] "8e906b02-e60e-470e-826d-f66e1996fd55"
## [418] "9cd6f2f4-191a-4fd3-a5c0-d8cef7dc9241"
## [419] "badea590-a44e-4fb2-a4d8-a5bc231cf64d"
## [420] "5f2dfca2-faae-4899-800b-94380aaaadd2"
## [421] "fe024e3d-db16-4e6e-a360-37888c5ba622"
## [422] "e6811a2c-5f56-48fb-8c68-d443a808d45e"
## [423] "4313e540-8957-49fa-962d-d3e9c9904b12"
## [424] "320f7be3-8b3d-4571-bb58-4011cb9629ba"
## [425] "eb333e5e-bdaa-4116-9640-cc8d2a7d72a5"
## [426] "0a278b12-de75-4c0a-8fb0-04d9368e306c"
## [427] "906bff07-4952-48d3-b4e9-7b825835ca49"
## [428] "4c9f62fc-01ae-4e32-baa9-eac30c536601"
## [429] "9aa333aa-cb6a-4c49-86d2-27edd05adc1e"
## [430] "302ecc56-e8b6-404a-9b8e-ebd10b9b9186"
## [431] "056dcea8-6daf-4fc6-9ae8-88207c3dcd8a"
## [432] "4ce4766f-3af9-4dff-89ac-5acb402479ab"
## [433] "a1ade888-3781-46bc-bc83-d3f5aa7dd16b"
## [434] "8f7b71bd-b307-4949-b95c-edceff0ff7ee"
## [435] "ab893325-afcd-4017-bd93-a307413c5cf3"
## [436] "6f59b20d-37a2-4f45-bc33-fd193c171e3c"
## [437] "2c1b917d-7b85-4c2e-8388-3c3b23f2f1a1"
## [438] "8ecb7219-b926-46c2-b0fe-b95d0154ae1c"
## [439] "b584c4e4-b8af-4f83-9883-67400d571505"
## [440] "13769705-13cc-48fe-a571-4855f47be61a"
## [441] "446934f5-c5cb-4216-ba77-2b4cde9daa60"
## [442] "1d1624e5-833b-4c0e-9fe1-189de5df3d34"
## [443] "0a54ed10-c3b3-4698-9432-07958f53b207"
## [444] "d4fba1d8-8b34-423d-8223-4d9686bcf1dc"
## [445] "44886096-9d58-4196-83f5-bfb63494d7a5"
## [446] "494c9dbe-71c0-4117-8647-8bd99d22b8df"
## [447] "38d0da92-4e66-4e4b-b918-8c96170777f4"
## [448] "560a662c-d9cd-45a7-8ab1-8d9a5cbd140e"
## [449] "9a9880ca-3bba-4be9-aeb4-fc19068cbe50"
## [450] "26f2594b-cbb7-4afb-ab41-64d11302759d"
## [451] "4cfe9246-a5e2-4b29-9003-37f92b92e8b7"
## [452] "29966089-2692-4530-9f47-6fb83f55a1f7"
## [453] "ce9a3eb4-47eb-4c70-8b7c-742abc673c65"
## [454] "b7fd7ab8-05bd-4270-847e-e7ffc580186d"
## [455] "38456a8e-a44f-4bf5-bfce-7eb39643385d"
## [456] "b11e92a1-0198-456a-b971-a2c6dac6a896"
## [457] "9ba7a58a-5e6f-42ae-9a15-199b5d62c4fe"
## [458] "7f37f43a-6457-43dd-925f-667bec41bf82"
## [459] "61b0abce-07be-4506-b0f5-49de8d8d9cb0"
## [460] "9bc26ec6-67e0-47b1-ab40-e817a95d8818"
## [461] "8a7dec69-49fc-42d0-8b58-fcf22a9e9932"
## [462] "a6dc42c2-3900-4651-a75a-13e33174e281"
## [463] "03225d48-d8f3-4795-a8f5-d0c5f4e2b483"
## [464] "b58f26c1-5e02-445b-8b75-ecf886e49199"
## [465] "27ec81a6-20e4-4333-ad48-0ac4d0edc79f"
## [466] "1843548b-e1d7-40e2-8212-f74ae8a71486"
## [467] "4e6e177a-126e-4c71-833c-c86d71f445b8"
## [468] "ebf4cb03-60a0-40e1-afc3-976252e62719"
## [469] "dc37f1ec-0366-40b3-a773-d0d1ef9630fd"
## [470] "f804dba3-3ee1-4639-a3e5-68da7c5c395a"
## [471] "3cab1bfb-2d6b-4a53-a18a-73f39d62969f"
## [472] "ba9b45ee-cd4e-46f2-98c1-c21483a13dac"
## [473] "1ed86869-6179-4b07-a3cb-8e10da440e98"
## [474] "82620fa0-ce02-4d1d-844f-6e91011a77ea"
## [475] "3afc6b3c-cd13-4a81-9f3a-413c6301e71d"
## [476] "7c0d69e9-ccd4-4017-84a3-6c4dccad694b"
## [477] "74ff6f92-7f9d-4c3f-822d-38c412d55dc3"
## [478] "1d3303e3-c0ef-4fcb-9d56-1661ccc78b76"
## [479] "e16dacc6-913a-432e-89ce-7b994c0d1bf2"
## [480] "7717a14b-b916-436e-913c-48e16e8f1216"
## [481] "e105d42b-da54-40eb-8851-4ba686f4a1c6"
## [482] "6ad0adcd-aedb-4a6c-84da-fb39932fd851"
## [483] "cf0fff8d-e717-49a6-8eb0-e65aaa231381"
## [484] "838be64d-a849-4d27-8aec-bca0a473e695"
## [485] "2bd27d69-ee8e-44c9-81a6-892b4f8465e1"
## [486] "7ba24396-201c-440b-86c5-9605b1706917"
## [487] "15c817eb-b169-4795-91de-8cf8539fb49a"
## [488] "736bcb6f-e62a-4a21-9ee5-60dbc03e6deb"
## [489] "05e7431c-6cd2-4980-9756-9b07fe4eae71"
## [490] "b4c5f573-223f-4150-a8cc-237e4d9e290b"
## [491] "6b6391d5-7ef3-4a74-aa2f-458c0a6a4f85"
## [492] "2c0c4120-bb8b-4b8f-8359-d1ffb244818e"
## [493] "b5291134-5055-45d8-9130-225d862feb20"
## [494] "2164a8a1-c467-4157-abee-c9bf146004e9"
## [495] "c2b2199f-1843-4502-a000-f20cf19bddb0"
## [496] "fcc5b0a6-34d9-4515-b81e-2c4ff17a5086"
## [497] "689d9753-f707-41ee-9d7f-ceaeb1b035d6"
## [498] "0b5e6e75-802a-49cf-ab71-935d65eacbbc"
## [499] "e2d0a861-6dd9-487d-9fc5-c13f33e0bd82"
## [500] "b0170e94-2026-4e8f-9ec5-f7c804152130"
## [501] "a8b3b5c3-cdba-4eb9-9444-c2f949507efd"
## [502] "219c0dc7-bba6-4f52-b009-f6cff46c8814"
## [503] "90b1a5e8-f411-4b39-a2f4-4c2c574b02ec"
## [504] "db9e46b7-a6f8-4db7-925b-7efb18b472a3"
## [505] "55003328-8b1e-459c-946b-8faf90504fdc"
## [506] "1d6c1eed-e6ca-477d-8192-4f629dd9d6ba"
## [507] "7b4f0ef6-a9ce-4177-acc5-38f8f93e85f6"
## [508] "6f8c1a2d-ad25-4b95-9024-6e16347f00c4"
## [509] "ea0efc32-7c3c-43ab-a007-60656073f9e8"
## [510] "8916c000-9fcc-4d87-b751-f3027b0e2082"
## [511] "963d146f-2960-4b02-9e0a-66cd09ee1605"
## [512] "2d6e53d9-9e17-48f2-97e7-154acdb996b7"
## [513] "a6097554-fca2-4853-b853-b159d9a8f572"
## [514] "3aaf5759-78cb-4596-b154-f9b5a2bb2726"
## [515] "3ea94763-bc87-4097-9cda-c08dafd8a8d5"
## [516] "d4075a1b-b12e-4b2d-9236-e118140be800"
## [517] "84fcf057-7410-4702-831d-2e88b9eaf616"
## [518] "6015e442-444a-487e-abd1-de3809560d3a"
## [519] "9f2d457e-3b18-4832-bfd0-a5cfa73aae44"
## [520] "14d0efdc-f518-4a9d-9b1d-b7dbbccf92ad"
## [521] "47e535fc-3b3a-4acf-974c-3956415bb101"
## [522] "74a1293a-29ab-418e-bded-fcb377b4aa6b"
## [523] "9f974332-a63f-4b58-8bfe-40b941a79e1e"
## [524] "0fa1a18c-2afe-459c-b7d8-c05461c79c8a"
## [525] "e44c6002-f73e-4a1a-a19e-1a0de9cbc742"
## [526] "4ec3713a-2424-490b-a46c-1f8df8ead736"
## [527] "7f73cb5d-6bb4-49e9-92af-8d9ce97bc66b"
## [528] "c8055d9c-94b8-43b4-bd1d-7aad4b97392f"
## [529] "d8450d57-dece-448a-88e1-d32a7d054b2e"
## [530] "e3006c17-4e4c-454b-b38a-2f0ea59a43ef"
## [531] "9e48abb1-3331-48d2-90ef-369091ac3963"
## [532] "26f31e18-1991-40eb-85fc-c9aa406b135b"
## [533] "cb540c5d-54b1-4dc3-add1-8b271c11352e"
## [534] "56351b3c-5897-421d-854f-ea77692b1234"
## [535] "bf6d3850-4cac-4073-b255-7e9ae8e43773"
## [536] "8d47a28e-dd61-4830-8d26-fd1b683d4acc"
## [537] "79a3b463-4766-4521-8b70-524aad54db8b"
## [538] "cf039ad6-7b2c-4732-bdc1-528060d45815"
## [539] "60873cd7-d373-459b-9642-a5dfe91b0fbc"
## [540] "d2376462-b4d6-4d6b-a0e9-d86f93629cf9"
## [541] "6addf87b-c43b-42be-8a76-44efa17bc0a2"
## [542] "d9562416-80e6-4aad-84bb-48c1d0d8f30a"
## [543] "f30fbc5c-4743-483d-857b-71c3162b602d"
## [544] "ce032981-672b-438e-a0b8-ac3ed8cbb98f"
## [545] "ba8077a4-2848-4210-9db6-4681bc043a5d"
## [546] "07a3fca4-5d74-4994-b269-842c5ab5bbaf"
## [547] "29642b15-19bf-47f9-b462-5701ec2f4c31"
## [548] "f75d6632-7114-409f-834b-9b9f8d2a6a39"
##
## $Encounter.verbatimLocality
## [1] "praia_grande" NA "anjos" "forno"
## [5] "prainha" "anequim" "pontal" "pedra_vermelha"
## [9] "cardeiro" "porcos_saltador" "porcos_ponta_sul" "gracainha"
## [13] "ilha_farol" "enseada_abobora" "porcos" "ponta_leste"
## [17] "boqueirao"
##
## $Encounter.year
## [1] "2021" "2020" "2019" "2018" "2017" "2016" "2015" "2014" "2013" "2012"
## [11] "2010" "2009" "2008" "2007" "2006"
##
## $Encounter.month
## [1] "9" "8" "6" "4" "3" "11" "10" "5" "2" "1" "12" "7"
##
## $Encounter.day
## [1] "30" "0" "17" "18" "26" "25" "5" "31" "20" "19" "9" "23" "13" "14" "3"
## [16] "16" "10" "21" "1" "29" "15" "12" "11" "4" "28" "27" "7" "6" "2" "8"
## [31] "24" "22"
##
## $Encounter.behavior
## [1] NA "resting" "foraging"
##
## $Encounter.genus
## [1] "Chelonia" "Eretmochelys"
##
## $Encounter.specificEpithet
## [1] "mydas" "imbricata"
##
## $Encounter.occurrenceRemarks
## [1] "left" "right" "both"
##
## $Encounter.mediaAsset0
## [1] "744.jpeg" "745.jpeg" "7.jpg" "741.jpeg" "743.jpeg" "742.jpeg"
## [7] "740.jpeg" "696.jpeg" "746.jpeg" "747.jpeg" "691.jpg" "693.jpg"
## [13] "690.jpg" "694.jpg" "681.jpg" "682.jpg" "676.jpg" "675.jpg"
## [19] "687.jpg" "686.jpg" "685.jpg" "678.jpg" "679.jpg" "677.jpg"
## [25] "674.jpg" "673.jpg" "672.jpg" "669.jpg" "671.jpg" "670.jpg"
## [31] "668.jpg" "667.jpg" "666.jpg" "664.JPG" "665.JPG" "712.JPG"
## [37] "716.JPG" "711.JPG" "710.JPG" "713.JPG" "714.JPG" "715.JPG"
## [43] "680.JPG" "703.JPG" "709.JPG" "708.JPG" "705.JPG" "706.JPG"
## [49] "704.JPG" "702.JPG" "728.JPG" "721.JPG" "719.JPG" "718.JPG"
## [55] "737.JPG" "738.JPG" "739.JPG" "736.JPG" "733.JPG" "717.JPG"
## [61] "720.JPG" "735.JPG" "726.JPG" "722.JPG" "727.JPG" "731.JPG"
## [67] "723.JPG" "725.JPG" "729.JPG" "689.JPG" "688.JPG" "683.JPG"
## [73] "684.JPG" "663.JPG" "660.JPG" "700.JPG" "698.JPG" "697.JPG"
## [79] "661.JPG" "662.JPG" "701.JPG" "655.JPG" "654.JPG" "653.JPG"
## [85] "656.JPG" "649.JPG" "650.JPG" "651.JPG" "652.jpg" "657.JPG"
## [91] "647.JPG" "646.JPG" "645.JPG" "644.JPG" "643.JPG" "640.JPG"
## [97] "639.JPG" "641.JPG" "637.jpg" "635.jpg" "630.jpeg" "629.jpeg"
## [103] "615.jpeg" "612.jpg" "610.jpg" "609.jpg" "611.jpg" "613.jpeg"
## [109] "625.jpg" "626.jpg" "621.jpg" "617.jpg" "619.jpg" "622.jpg"
## [115] "620.jpg" "627.jpg" "624.jpg" "623.jpg" "634.jpg" "631.jpg"
## [121] "600.jpg" "632.jpg" "582.jpeg" "584.jpg" "583.jpg" "597.jpeg"
## [127] "575.jpeg" "580.jpeg" "577.jpeg" "596.jpg" "492.jpg" "491.jpg"
## [133] "495.jpg" "490.jpg" "539.jpg" "489.jpg" "513.jpg" "462.jpg"
## [139] "482.jpg" "585.jpg" "481.jpg" "529.jpeg" "531.jpg" "511.jpg"
## [145] "512.jpg" "537.jpg" "540.jpg" "352.JPG" "365.jpg" "348.jpeg"
## [151] "338.JPG" "532.jpg" "340.JPG" "339.JPG" "346.jpeg" "541.jpg"
## [157] "364.jpg" "530.jpg" "376.jpg" "359.jpg" "278.jpg" "363.jpg"
## [163] "159.jpg" "266.jpg" "592.jpg" "391.jpg" "240.jpg" "285.jpg"
## [169] "173.jpg" "228.jpg" "245.jpg" "608.jpg" "242.jpg" "231.jpg"
## [175] "155.jpg" "374.jpg" "293.jpg" "360.jpg" "414.jpg" "460.jpg"
## [181] "276.jpg" "312.jpg" "252.jpg" "251.jpg" "141.jpeg" "136.jpeg"
## [187] "151.jpg" "604.jpg" "152.jpg" "153.jpg" "256.jpg" "255.jpg"
## [193] "361.jpg" "366.jpg" "595.jpg" "401.jpg" "400.jpg" "399.jpg"
## [199] "479.jpg" "275.jpg" "263.jpg" "147.jpg" "154.jpg" "239.jpg"
## [205] "477.jpg" "133.JPG" "274.jpg" "594.jpg" "257.jpg" "207.jpg"
## [211] "254.jpg" "140.jpg" "134.jpeg" "341.jpg" "204.jpg" "132.JPG"
## [217] "379.jpg" "235.jpg" "138.jpg" "517.jpg" "343.jpg" "139.jpg"
## [223] "543.jpg" "268.jpg" "265.jpg" "264.jpg" "258.jpg" "148.jpg"
## [229] "249.jpg" "163.jpg" "237.jpg" "190.jpg" "171.jpg" "412.jpg"
## [235] "606.jpg" "162.jpg" "607.jpg" "161.jpg" "322.jpg" "395.jpg"
## [241] "357.jpg" "358.jpg" "164.jpg" "565.jpg" "458.jpg" "187.jpg"
## [247] "176.jpg" "211.jpg" "601.jpg" "404.jpg" "195.jpg" "405.jpg"
## [253] "82.JPG" "91.jpg" "419.jpg" "383.jpg" "84.jpeg" "202.jpg"
## [259] "536.jpg" "402.jpg" "238.jpg" "318.jpg" "381.jpg" "382.jpg"
## [265] "350.jpg" "380.jpg" "416.jpg" "415.jpg" "271.jpg" "418.jpg"
## [271] "313.jpg" "506.jpg" "542.jpg" "502.jpg" "410.jpg" "297.jpg"
## [277] "291.jpg" "406.jpg" "321.jpg" "169.jpg" "325.jpg" "145.jpg"
## [283] "306.jpg" "80.jpeg" "304.jpg" "261.jpg" "501.jpg" "389.jpg"
## [289] "290.jpg" "284.jpg" "563.jpg" "199.jpg" "548.jpg" "453.jpg"
## [295] "146.jpg" "315.jpg" "553.jpg" "303.jpg" "387.jpg" "279.jpg"
## [301] "371.jpg" "250.jpg" "323.jpg" "510.jpg" "61.jpg" "311.jpg"
## [307] "378.jpg" "377.jpg" "182.jpg" "179.jpg" "296.jpg" "165.jpg"
## [313] "484.jpg" "485.jpg" "487.jpg" "373.jpg" "559.jpg" "175.jpg"
## [319] "326.jpg" "76.jpg" "351.jpg" "224.jpg" "508.jpg" "191.jpg"
## [325] "638.jpg" "505.jpg" "413.jpg" "347.jpg" "180.jpg" "500.jpg"
## [331] "498.jpg" "208.jpg" "388.jpg" "564.jpg" "177.jpg" "496.jpg"
## [337] "160.jpg" "198.jpg" "344.jpg" "247.jpg" "558.jpg" "72.JPG"
## [343] "277.jpg" "192.jpg" "225.jpg" "349.jpg" "567.jpg" "299.jpg"
## [349] "298.jpg" "469.jpg" "214.jpg" "475.jpg" "451.jpg" "470.jpg"
## [355] "438.jpg" "218.jpg" "259.jpg" "450.jpg" "178.jpg" "70.JPG"
## [361] "557.jpg" "464.jpg" "440.jpg" "69.jpg" "158.jpeg" "203.jpg"
## [367] "446.jpg" "566.jpg" "262.jpg" "260.jpg" "535.jpg" "456.jpg"
## [373] "213.jpg" "283.jpg" "454.jpg" "463.jpg" "447.jpg" "472.jpg"
## [379] "183.jpg" "471.jpg" "445.jpg" "217.jpg" "216.jpg" "200.jpg"
## [385] "441.jpg" "562.jpg" "466.jpg" "408.jpg" "174.jpg" "633.jpg"
## [391] "186.jpg" "307.jpg" "222.jpg" "335.jpg" "221.jpg" "227.jpg"
## [397] "63.jpg" "229.jpg" "181.jpg" "356.jpg" "324.jpg" "337.jpg"
## [403] "561.jpg" "386.jpg" "129.jpg" "280.jpg" "568.jpg" "572.jpg"
## [409] "547.jpg" "309.jpg" "302.jpg" "334.jpg" "571.jpg" "398.jpg"
## [415] "555.jpg" "62.jpg" "573.jpg" "320.jpg" "193.jpg" "184.jpg"
## [421] "166.jpg" "519.jpg" "59.jpg" "58.jpg" "527.jpg" "57.JPG"
## [427] "522.jpg" "189.jpg" "234.jpg" "427.jpg" "556.jpg" "429.jpg"
## [433] "423.jpg" "385.jpg" "167.jpg" "435.jpg" "232.jpg" "443.jpg"
## [439] "436.jpg" "425.jpg" "422.jpg" "196.jpg" "538.jpg" "420.jpg"
## [445] "526.jpg" "448.jpg" "523.jpg" "433.jpg" "520.jpg" "201.jpg"
## [451] "220.jpg" "437.jpg" "514.jpg" "528.jpg" "525.jpg" "370.jpg"
## [457] "390.jpg" "54.jpg" "233.jpg" "432.jpg" "424.jpg" "421.jpg"
## [463] "215.jpg" "586.jpg" "331.jpg" "587.jpg" "210.jpg" "434.jpg"
## [469] "431.jpg" "230.jpg" "53.jpg" "549.jpg" "411.jpg" "327.jpg"
## [475] "51.jpg" "397.jpg" "544.jpg" "367.jpg" "394.jpg" "409.jpg"
## [481] "49.jpg" "50.jpg" "48.jpg" "47.JPG" "43.jpg" "45.jpg"
## [487] "44.jpg" "368.jpg" "332.jpg" "476.jpg" "392.jpg" "42.jpg"
## [493] "41.jpg" "236.jpg" "112.JPG" "354.jpg" "40.jpg" "111.JPG"
## [499] "336.jpg" "126.jpg" "110.JPG" "39.jpg" "38.JPG" "109.JPG"
## [505] "106.JPG" "329.jpg" "36.jpg" "333.jpg" "533.jpg" "35.jpg"
## [511] "105.jpg" "122.jpg" "123.jpg" "103.JPG" "104.JPG" "31.JPG"
## [517] "33.JPG" "30.jpg" "372.jpg" "534.jpg" "28.JPG" "27.jpg"
## [523] "25.jpg" "98.JPG" "101.JPG" "102.JPG" "117.JPG" "24.JPG"
## [529] "22.JPG" "23.JPG" "20.JPG" "21.JPG" "15.JPG" "12.jpg"
## [535] "97.jpg" "11.jpg" "9.jpg" "10.jpg" "8.jpg" "6.jpg"
## [541] "4.jpg" "96.jpg" "5.jpg" "328.jpg" "3.JPG" "2.JPG"
## [547] "1.JPG"
##
## $Encounter.mediaAsset1
## [1] NA "695.jpeg" "707.JPG" "734.JPG" "732.JPG" "724.JPG"
## [7] "730.JPG" "669.jpg" "636.jpg" "616.jpeg" "614.jpeg" "628.jpg"
## [13] "599.jpeg" "598.jpeg" "576.jpeg" "578.jpeg" "494.jpg" "480.jpg"
## [19] "345.jpeg" "267.jpg" "172.jpg" "384.jpg" "142.jpeg" "273.jpg"
## [25] "593.jpg" "135.jpeg" "342.jpg" "396.jpg" "602.jpg" "92.JPG"
## [31] "403.jpg" "272.jpg" "417.jpg" "507.jpg" "503.jpg" "292.jpg"
## [37] "168.jpg" "316.jpg" "483.jpg" "486.jpg" "488.jpg" "509.jpg"
## [43] "473.jpg" "499.jpg" "497.jpg" "439.jpg" "157.jpeg" "185.jpg"
## [49] "301.jpg" "426.jpg" "552.jpg" "393.jpg" "99.JPG"
Configurando a data. Em caso de ausência do dia, foi padronizado uso do dia 15
originalenctable$Encounter.day[originalenctable$Encounter.day==0] <- 15
tabledate <- unite(originalenctable, Encounter.year, Encounter.month, Encounter.day, col = "Date", sep = "-")
tabledate$Date <- factor(tabledate$Date)
tabledate$Date <- as.Date(tabledate$Date, format = "%Y-%m-%d")
Definindo qual(is) lateral(is) os indivíduos têm ao longo do banco de dados
tablesides <- tabledate %>%
filter(!is.na(Name0.value)) %>%
group_by(Name0.value) %>%
mutate(Sides = case_when(any(str_detect(Encounter.occurrenceRemarks,"both")|n_distinct(Encounter.occurrenceRemarks) > 1) ~ 'both',
TRUE ~ Encounter.occurrenceRemarks )) %>%
ungroup
Definindo quais indivíduos já foram revistos
tableresight <- tablesides %>%
filter(!is.na(Name0.value)) %>%
group_by(Name0.value) %>%
mutate(Resight = case_when (any(n_distinct(Occurrence.occurrenceID) > 1) ~ 'yes',
TRUE ~ 'no' ))
Tabela final com o número total de indivíduos
tableturtlesmax <- tableresight %>%
filter(!is.na(Name0.value))
Número de fotos que foram avaliadas para criar esse banco de dados
tableturtlesmax %>%
filter(!is.na(Encounter.mediaAsset0)) %>%
group_by(Encounter.genus) %>%
dplyr::summarise(n_distinct (Encounter.mediaAsset0))
## # A tibble: 2 x 2
## Encounter.genus `n_distinct(Encounter.mediaAsset0)`
## <chr> <int>
## 1 Chelonia 438
## 2 Eretmochelys 109
tableturtlesmax %>%
filter(!is.na(Encounter.mediaAsset1)) %>%
group_by(Encounter.genus) %>%
dplyr::summarise(n_distinct (Encounter.mediaAsset1))
## # A tibble: 2 x 2
## Encounter.genus `n_distinct(Encounter.mediaAsset1)`
## <chr> <int>
## 1 Chelonia 41
## 2 Eretmochelys 11
Contando o número de indivíduos distintos para cada espécie, de acordo com a(s) lateral(is) que os indivíduos foram registrados.
tableturtlesmax %>%
filter(!is.na(Name0.value)) %>%
filter(Encounter.genus == "Chelonia") %>%
distinct (Name0.value, .keep_all= TRUE) %>%
group_by(Sides) %>%
dplyr::summarise(count = n())
## # A tibble: 3 x 2
## Sides count
## <chr> <int>
## 1 both 30
## 2 left 126
## 3 right 130
tableturtlesmax %>%
filter(!is.na(Name0.value)) %>%
filter(Encounter.genus == "Eretmochelys") %>%
distinct (Name0.value, .keep_all= TRUE) %>%
group_by(Sides) %>%
dplyr::summarise(count = n())
## # A tibble: 3 x 2
## Sides count
## <chr> <int>
## 1 both 9
## 2 left 22
## 3 right 14
Para evitar possível replicação de indivíduos, é preciso selecionar o número mínimo de indivíduos confirmados. Esse número é o valor dos indivíduos identificados que possuem as duas laterais ‘both’ somado com a lateral que mais possui indivíduos identificados. Nesse caso ‘right’ para C. mydas e ‘left’ para E. imbricata.
tableturtlesmin <-tableturtlesmax %>%
filter(!is.na(Name0.value)) %>%
filter(Sides %in% c('both', 'right') & Encounter.genus == "Chelonia" |
Sides %in% c('both', 'left') & Encounter.genus == "Eretmochelys")
Número de fotos por ano, para cada espécie
tableturtlesmin %>%
distinct (Name0.value, .keep_all= TRUE) %>%
mutate(year = format(Date, "%Y")) %>%
group_by(year) %>%
ggplot(., aes(x=year, fill=Encounter.genus))+
geom_bar(width=.8, position = position_dodge2(preserve = "single")) +
scale_x_discrete(name = "Ano", breaks = seq(2006, 2021, 1)) +
scale_y_continuous(name = "Fotos", breaks = seq(0, 100, 20),expand = c(0,0,0,1))
Número de Indivíduos por ano, para cada espécie
tableturtlesmin %>%
distinct (Name0.value, .keep_all= TRUE) %>%
mutate(year = format(Date, "%Y")) %>%
group_by(year) %>%
ggplot(., aes(x=year, fill= Encounter.genus))+
geom_bar() +
scale_y_continuous(name = "Indivíduos", breaks = seq(0, 110, 10), expand = c(0,0,0,15))+
scale_x_discrete(name = "Ano")+
theme(legend.position = "none")+
facet_grid(rows = vars(Encounter.genus),scales = "free", space = "free")
Quantidade e frequência de indivíduos que foram revistos
tableturtlesmin %>%
filter(!is.na(Encounter.mediaAsset0)) %>%
distinct (Name0.value, .keep_all= TRUE) %>%
group_by(Encounter.genus, Resight) %>%
dplyr::summarise(count = n()) %>%
ungroup() %>%
mutate(freq = count / sum(count))
## `summarise()` has grouped output by 'Encounter.genus'. You can override using the `.groups` argument.
## # A tibble: 4 x 4
## Encounter.genus Resight count freq
## <chr> <chr> <int> <dbl>
## 1 Chelonia no 116 0.607
## 2 Chelonia yes 44 0.230
## 3 Eretmochelys no 24 0.126
## 4 Eretmochelys yes 7 0.0366
Presença dos indivíduos revistos nas fotos
tableturtlesmin %>%
filter(!is.na(Encounter.mediaAsset0)) %>%
group_by(Encounter.genus, Resight) %>%
dplyr::summarise(n_distinct (Encounter.mediaAsset0))
## `summarise()` has grouped output by 'Encounter.genus'. You can override using the `.groups` argument.
## # A tibble: 4 x 3
## # Groups: Encounter.genus [2]
## Encounter.genus Resight `n_distinct(Encounter.mediaAsset0)`
## <chr> <chr> <int>
## 1 Chelonia no 116
## 2 Chelonia yes 168
## 3 Eretmochelys no 24
## 4 Eretmochelys yes 65
tableturtlesmin %>%
filter(!is.na(Encounter.mediaAsset1)) %>%
group_by(Encounter.genus, Resight) %>%
dplyr::summarise(n_distinct (Encounter.mediaAsset1))
## `summarise()` has grouped output by 'Encounter.genus'. You can override using the `.groups` argument.
## # A tibble: 4 x 3
## # Groups: Encounter.genus [2]
## Encounter.genus Resight `n_distinct(Encounter.mediaAsset1)`
## <chr> <chr> <int>
## 1 Chelonia no 8
## 2 Chelonia yes 32
## 3 Eretmochelys no 4
## 4 Eretmochelys yes 7
Filtrando apenas os indivíduos que foram revistos
turtlesresighted <- tableturtlesmin %>%
filter(Resight == "yes")
Identificando a data dos encontros
table_sum <- turtlesresighted %>%
group_by(Date, Name0.value, Encounter.genus) %>%
dplyr::summarise(count = n()) %>%
mutate_at(vars(count), funs(factor))
## `summarise()` has grouped output by 'Date', 'Name0.value'. You can override using the `.groups` argument.
## Warning: `funs()` was deprecated in dplyr 0.8.0.
## Please use a list of either functions or lambdas:
##
## # Simple named list:
## list(mean = mean, median = median)
##
## # Auto named with `tibble::lst()`:
## tibble::lst(mean, median)
##
## # Using lambdas
## list(~ mean(., trim = .2), ~ median(., na.rm = TRUE))
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was generated.
Calculando o intervalo entre o primeiro e último encontro dos indivíduos.
table_range <- table_sum %>%
group_by(Name0.value, Encounter.genus) %>%
dplyr::summarise(min = min(Date),
max = max(Date)) %>%
ungroup() %>%
mutate(diff_dias=max-min) %>%
mutate(diff_meses=diff_dias/(365.25/12)) %>%
mutate(diff_anos=diff_dias/(365)) %>%
mutate_at(vars(diff_meses,diff_anos), round, 1) %>%
mutate_if(is.difftime,as.numeric)
## `summarise()` has grouped output by 'Name0.value'. You can override using the `.groups` argument.
Calculando descritores do intervalo entre o primeiro e último encontro de cada indivíduo
describeBy(table_range$diff_anos, table_range$Encounter.genus)
##
## Descriptive statistics by group
## group: Chelonia
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 44 1.73 1.52 1.65 1.58 1.85 0 5.4 5.4 0.66 -0.57 0.23
## ------------------------------------------------------------
## group: Eretmochelys
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 7 2.66 2.07 2.4 2.66 1.78 0.1 5.6 5.5 0.32 -1.7 0.78
median <- ddply(table_range, .(Encounter.genus), summarise, median = median(diff_anos))
Histograma do intervalo entre os encontros com a mediana
ggplot(table_range, aes(x=diff_anos)) +
geom_histogram(binwidth= 1, alpha=.7, boundary = 0, aes(fill=Encounter.genus, color=Encounter.genus))+
scale_y_continuous(name = "Indivíduos",breaks = seq(0, 22, 2), expand = c(0,0,0,2))+
scale_x_continuous(name = "Intervalo (anos)",breaks = 1:6)+
geom_vline(data=median, aes(xintercept=median),
linetype="dashed")+
facet_grid (rows = vars(Encounter.genus),scales = "free", space = "free")+
theme(legend.position = "none")
Nessa etapa foi escolhido filtrar os indivíduos onde o intervalo entre o primeiro e último encontro é maior do que 12 meses.
table_range <- table_range %>%
filter ( diff_meses > 12 )
Selecionando os indivíduos de ‘table_range’ em ‘table_sum’
table_sum_ok <- table_sum %>%
filter(Name0.value %in% table_range$Name0.value)
Linha do tempo dos indivíduos, marcando todos os encontros
ggplotly (ggplot(table_sum_ok, aes(x = Date, y = Name0.value)) +
geom_segment(data = table_range, size = 1.6, alpha=.4,
aes(x = min, xend = max, y = Name0.value, yend = Name0.value))+
geom_point(aes(color=Encounter.genus), alpha=1, size=2.7) +
labs(x="Tempo", y="Indivíduos")+
scale_x_date(date_breaks = "3 months", date_labels = "%m/%Y")+
theme_light()+
theme(axis.text.x = element_text(angle = 45, hjust = .9, vjust = .9)))